Title
Leveraging crowd skills and consensus for collaborative web-resource labeling
Abstract
In this paper, we propose a three-stage approach called CLabel for enforcing collaborative web-resource labeling in form of a crowdsourcing process. In CLabel, the results of both crowdsourcing and automated tasks are combined into a coherent process flow. CLabel leverages on crowd preferences and consensus, for capturing the different interpretations that can be associated with a considered web resource in form of different candidate labels and for selecting the most agreed candidate(s) as the final result. CLabel succeeds to be particularly appropriate for application to labeling problems and scenarios where human feelings and preferences are decisive to select the answers (i.e., labels) supported by the majority of the crowd. Moreover, CLabel succeeds in providing label variety when multiple labels are required for a suitable resource annotation, thus avoiding duplicate or repetitive labels.
Year
DOI
Venue
2019
10.1016/j.future.2017.12.024
Future Generation Computer Systems
Keywords
Field
DocType
Crowdsourcing,Consensus-based web-resource labeling,Task design
Web resource,Annotation,Information retrieval,Computer science,Crowdsourcing,Distributed computing
Journal
Volume
ISSN
Citations 
95
0167-739X
0
PageRank 
References 
Authors
0.34
11
3
Name
Order
Citations
PageRank
Silvana Castano12120371.52
Alfio Ferrara271059.86
Stefano Montanelli342242.17